{"id":2787,"date":"2024-02-06T08:00:00","date_gmt":"2024-02-06T16:00:00","guid":{"rendered":"https:\/\/devblogs.microsoft.com\/azure-sql\/?p=2787"},"modified":"2024-02-06T08:00:00","modified_gmt":"2024-02-06T16:00:00","slug":"chat-with-your-data-azure-sql-database","status":"publish","type":"post","link":"https:\/\/devblogs.microsoft.com\/azure-sql\/chat-with-your-data-azure-sql-database\/","title":{"rendered":"Chat with your data in Azure SQL Database"},"content":{"rendered":"

Welcome to the exploration of how to chat with your data in Azure SQL Database. Being able to interact with your data more intuitively and conversationally can significantly enhance your data analysis and decision-making processes. This blog post will guide you through the process of setting up a chat interface for your Azure SQL Database, using an eCommerce database as an example. Whether you\u2019re a data scientist, a developer, or just a curious learner, this guide will provide you with a new perspective on interacting with your data.<\/p>\n

Create Azure AI Search<\/h2>\n

The first step is to create an Azure AI search resource, Learn more here<\/a>.<\/p>\n

Data Source<\/h2>\n

Our journey begins with our data source from Kaggle\u2019s product dataset<\/a>. This dataset has product names, descriptions, categories, prices, and more. It\u2019s the perfect playground for a chat interface, allowing users to ask about products, compare prices, and even get recommendations for products for an occasion or scenario. This data is loaded into the Azure SQL Database. In an e-commerce website, this database can be a sales and product catalog.<\/p>\n

\"Image<\/a><\/p>\n

Connect Azure SQL Database<\/h2>\n

To start chatting with our data, we first need to establish a connection to our Azure SQL Database. This is done by setting up a connection string, and a query. Once the connection string is set up, we can use it to establish a connection to the database. To learn more about how to connect Azure SQL Database to Azure Search using Indexers, read here<\/a>.<\/p>\n

Add search fields to an Index<\/h2>\n

In a search index, add fields that correspond to the fields in the SQL database. Ensure that the search index schema is compatible with the source schema by using equivalent data types. It will look like this:<\/p>\n

\"Image<\/a><\/p>\n

Create Indexer<\/h2>\n

Now that we have our index, we need an indexer to populate it. In Azure Search, an indexer is a crawler that automatically goes through our data source and populates our index. Once the indexer is up and running, our index will always be up-to-date with the latest data.<\/p>\n

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Indexing new, changed, and deleted rows<\/h2>\n<\/div>\n

If your SQL database supports\u00a0change tracking<\/a>, a search indexer can pick up just the new and updated content on subsequent indexer runs.<\/p>\n

To enable incremental indexing, set the “dataChangeDetectionPolicy” property in your data source definition. This property tells the indexer which change tracking mechanism is used on your table or view.<\/p>\n

For Azure SQL indexers, there are two change detection policies:<\/p>\n